Biology subjects

Cao, D.

Publications and source records attributed to Cao, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Granzyme B-based CAR T cells block metastasis by eliminating circulating tumor cells

Chimeric antigen receptor (CAR) T cells have limited efficacy against solid tumors due to the hostile microenvironment. Circulating tumor cells (CTCs) are essential to metastasis, which is the cause of most of cancer-related death. Here, we generated GrB-CAR T cells targeting membrane-bound HSP70 (mHSP70), a highly tumor-specific antigen detected in numerous cancers. GrB-CAR T cells exhibited potent cytotoxicity against a broad spectrum of cancer cell lines and stem-like cancer cells in vitro and effectively inhibited xenograft tumor growth in vivo. Importantly, GrB-CAR T cells markedly decreased the number of CTCs and, therefore, hindered cancer metastasis in spontaneous metastasis models with uncontrollable primary tumor growth, a scenario commonly encountered in clinical trials of CAR T therapies for solid tumors. Furthermore, despite the 100% homology between human and macaque HSP70 protein, the autotransplantation of macaque T cells expressing human GrB-CAR did not cause any obvious toxic effects. These results not only demonstrate GrB-CAR T cells as a safe and effective tactic with broad-spectrum anticancer activity, but also offer strong experimental evidence and proof-of-concept validation for CAR T cell-mediated metastasis inhibition by targeting CTCs.

immunology↗

bioRxiv2024

PackDock: a Diffusion Based Side Chain Packing Model for Flexible Protein-Ligand Docking

Structure-based drug design (SBDD) relies on accurate knowledge of protein structure and ligand-binding conformations. However, most of the static conformations obtained by advanced methods such as structural biology and de novo protein folding algorithms often dont meet the needs for drug design. We introduce PackDock, a flexible docking method that combines "conformation selection" and "induced fit" mechanisms in a two-stage docking pipeline. The core module of this method is PackPocket, which uses a diffusion model to explore the side-chain conformation space in ligand binding pockets, both with or without a ligand. We evaluate our method using several tests that reflect real-world application scenarios. (1) Side-chain packing and Re-docking experiments validate the ability of PackDock to predict accurate side-chain conformations and ligand conformations. (2) Cross-docking experiments with apo and non-homologous ligand-induced holo structures align with real docking scenarios, demonstrating PackDocks practical value. (3) Docking experiments with hypothetical models show that PackPocket can potentially conduct SBDD starting from protein sequence information only. Additionally, we found that PackDock can identify key amino acid conformation changes, which may provide insights for lead compound optimization. We demonstrate PackDock can accurately predict the complex conformations in various application scenarios, by combining the conformation selection theory and the induced fit theory, and by using the ability of PackPocket to accurately predict the side chain conformations in the pocket region. We believe this method can improve the usability of existing structures, providing a new perspective for the SBDD community.

bioinformatics↗

bioRxiv2024

Single-Nuclei RNA Sequencing Identifies Type C Low-Threshold Mechanoreceptors as Key Players in Paclitaxel-Induced Peripheral Neuropathy

Neuropathic pain triggered by chemotherapy poses a significant clinical challenge. Investigating cell type-specific alterations through single-cell transcriptome analysis holds promise in understanding symptom development and pathogenesis. In this study, we performed single nuclei RNA (snRNA) sequencing of dorsal root ganglions (DRG) to explore the molecular mechanism underlying paclitaxel-induced neuropathic pain. Mouse exposed to repeated paclitaxel doses developed persistent pain hypersensitivity lasting at least 21 days. The snRNA sequencing unveiled seven major cell types within DRGs, with neurons further subdivided into 12 distinct subclusters using known markers. Notably, type C low-threshold mechanoreceptors (C_LTMR) exhibited the most pronounced transcriptomic changes post-paclitaxel administration. Differential gene expression and Gene Ontology (GO) analysis highlighted suppressed potassium-related currents, microtubule transport, and mitochondrial functions in C_LTMR following paclitaxel treatment. Meanwhile, Gene Set Enrichment Analysis (GSEA) suggested increased Interleukin 17 production in C_LTMR after paclitaxel exposure. Pseudo-time analysis uncovered nine distinct states (state 1 to 9) of C_LTMR. State 1 exhibits higher prevalence in paclitaxel-treated mice and altered neurotransmission properties, likely contributing to paclitaxel-induced pain hypersensitivity. This comprehensive exploration sheds light on the molecular mechanisms driving paclitaxel-induced neuropathic pain, offering potential avenues for therapeutic intervention.

neuroscience↗

bioRxiv2023

SurfDock is a Surface-Informed Diffusion Generative Model for Reliable and Accurate Protein-ligand Complex Prediction

In the field of structure-based drug design, accurately predicting the binding conformation of ligands to proteins is a long-standing objective. Despite recent advances in deep learning yielding various methods for predicting protein-ligand complex structures, these AI-driven approaches frequently fall short of traditional docking methods in practice and often yield structures that lack physical and chemical plausibility. To overcome these limitations, we present SurfDock, an advanced geometric diffusion network, distinguished by its ability to integrate multiple protein representations including protein sequence, three-dimensional structural graphs, and surface-level details into its equivariant architecture. SurfDock employs a generative diffusion model on a non-Euclidean manifold, enabling precise optimization of molecular translations, rotations, and torsions for reliable binding poses generation. Complemented by a mixture density network for scoring using the same comprehensive representation, SurfDock achieves significantly improved docking success rates over all existing methods, excelling in both accuracy and adherence to physical constraints. Equipped with post-docking energy minimization as an optional feature, the plausibility of generated poses is further enhanced. Importantly, SurfDock demonstrates excellent generalizability to unseen proteins and extensibility to virtual screening tasks with state-of-the-art performance. We consider it a transformative contribution that could serve as an invaluable asset in structure-based drug design.

bioinformatics↗

bioRxiv2023

Single cell sequencing as a general variant interpretation assay

The human genome contains [~]70 million possible protein-altering variants, the vast majority of which are of uncertain clinical significance. Closing this gap is essential for accurate diagnosis of disease-causing variants and understanding their mechanisms of action. Towards this goal, we developed a pooled perturbation approach combining saturation mutagenesis with single cell RNA sequencing to map the effects of every single nucleotide variant in a gene. We sequenced [~]440,000 cells expressing variants in CDKN2A (p16INK4a), TP53, and SOD1, observing almost all possible protein-coding variants, with a mean of 61 cells per variant. Using single cell gene expression signatures, we show that each gene may contain multiple types of pathogenic variants that affect distinct downstream pathways. We demonstrate that single cell expression signatures outperform existing bulk experimental assays and computational models for predicting pathogenicity, and summarize both the utility and potential limitations of single cell sequencing as a general variant interpretation assay.

genomics↗

bioRxiv2023

Long-term abstinence reduces optimal energy required for transitions from the exogenous networks to the frontoparietal network in methamphetamine addicts

Methamphetamine (MA) use disorder is a chronic neurotoxic brain disease characterized by a high risk of relapse driven by intense cravings. However, the neurobiological signatures of cravings remain unclear, limiting the effectiveness of various treatment methods. Diffusion MRI (dMRI) scans from 62 MA users and 57 healthy controls (HC) were used in this study. The MA users were longitudinally followed up during their period of long-term abstinence (duration of long-term abstinence: 347.52{+/-}99.25 days). We systematically quantified the control ability of each brain region for craving-associated state transitions using network control theory from a causal perspective. Craving-associated structural alterations (CSA) were investigated through multivariate group comparisons and biological relevance analysis. The neural mechanisms underlying CSA were elucidated using transcriptomic and neurochemical analyses. We observed that long-term abstinence-induced structural alterations significantly influenced the state transition energy involved in the cognitive control response to external information, which correlated with changes in craving scores (r [~] 0.35, P <0.01). Our causal network analysis further supported the crucial role of the prefrontal cortex (PFC) in craving mechanisms. Notably, while the PFC is central to the craving, the CSAs were distributed widely across multiple brain regions (PFDR<0.05), with strong alterations in somatomotor regions (PFDR<0.05) and moderate alterations in high-level association networks (PFDR<0.05). Additionally, transcriptomic, chemical compounds, cell-type analyses, and molecular imaging collectively highlight the influence of neuro-immune communication on human craving modulation. Our results offer an integrative, multi-scale perspective on unraveling the neural underpinnings of craving and suggest that neuro-immune signaling may be a promising target for future human addiction therapeutics.

neuroscience↗

bioRxiv2023

The receptor VLDLR binds East Equine Encephalitis virus through multiple distinct modes

Eastern Equine Encephalitis virus (EEEV) is an alphavirus that can cause severe diseases in infected humans. The very low-density lipoprotein receptor (VLDLR) was recently identified as a receptor of EEEV. Herein, we performed cryo-electron microscopy structural and biochemistry studies on the specific interactions between EEEV and VLDLR. Our results show that VLDLR binds EEEV at three different sites A, B and C through its membrane-distal 8 LDLR class A (LA) repeats (LA1-8). Site A is located in the cleft in between the E1-E2 heterodimers of the surface trimeric spikes. Site B is located near the connecting {beta} ribbon in between the B and A-C domains of E2 and is in proximity to site A, while site C is on the domain B of E2. LA1 and LA5 specifically recognize site A, whereas LA2, LA3 and LA6 can bind both sites A and C. The binding of VLDLR LAs to EEEV is in complex modes. The LA1-2 mediated binding plays a critical role in mediating virus entry. The mutation W132G of VLDLR impairs the binding of LA3, drives the switch of the binding modes, and significantly enhances the attachment of EEEV to the cell. The W132G variant of VLDLR could be identified in human genome and SNP sequences, implying that people with similar mutations in VLDLR may be highly susceptible to EEEV infection.

microbiology↗

bioRxiv2023

Bio-Mol:Pretraining Multimodality Bioactivity Profile for Enhancing Small Molecule Property Prediction

Non-optimized pharmacokinetic parameters serve as the primary cause of failure in clinical trials of drugs. Therefore, the successful prediction of pharmacokinetic parameters during the pre-clinical stage is crucial for the success of drug candidates. Conventional methods primarily rely on 2D structural information, while advanced models extend the features to other structural-related information or use advanced computational models to improve prediction accuracy. However, to gain a comprehensive understanding of small molecules, integrating bioactivity profiles with chemical structural information is essential. One significant challenge in this integration is the high proportion of missing values within experimentally validated bioactivity profiles for most small molecules. To address this challenge, we introduce Bio-Mol, an artificial intelligence model designed to effectively handle this issue. Bio-Mol utilizes a pretrain and finetune strategy, enabling the incorporation of a large proportion of missing bioactivity profiles during the small molecule representation learning process. Comprehensive evaluations of Bio-Mol demonstrate a notable improvement in predicting molecule properties. The integration of missing bioactivity profiles enhances the AUROC of average 5.2% compared to the previous state-of-the-art models predictions. Furthermore, we explore the potential of Bio-Mol in predicting synergistic drug combinations, highlighting its versatility and broader applications in the field of drug discovery. The successful implementation of Bio-Mol showcases its efficacy in over-coming the challenges posed by missing bioactivity profile data. This model paves the way for optimizing small molecule pharmacokinetics prediction, providing valuable insights for drug development and discovery processes.

bioinformatics↗

bioRxiv2023

Prominent contributions of selective neuronal subtypes to pediatric drug-resistant focal dysplasia

About 75% cases of epilepsy begin during childhood, and 10 - 30% of pediatric epilepsy patients are resistant to drug treatment. The predominant seizure type in children is focal cortical dysplasia (FCD) which is highly associated with drug-resistant epilepsy, but its underlying cause is poorly understood. We performed single-cell RNA sequencing and patch-clamp recording on fresh brain tissues obtained from pediatric FCD patients shortly after surgery to reveal critical factors contributing to FCD. We report that known epilepsy genes or significant transcriptomic alterations occur in only a few neuronal subgroups, suggesting that epilepsy-associated neurons cluster into only a few neuronal subtypes. These epilepsy-subtypes displayed significant epilepsy-related transcriptomic alterations, especially in the genes associated with excitation/inhibition balance and neuron functional signal pathways. Among eight epilepsy-subtypes, L2_4_CUX2_YWHAH and PVALB_RGS5 subtypes showed the most prominent alterations in FCD patient tissues. Supporting PV-neurons being important, recording from fast-spiking/parvalbumin-containing neurons in acute FCD patient brain slices revealed reduced excitatory synaptic inputs, implicating lower activity in these neurons and fewer synaptic inputs onto them. A higher percentage of mitochondria genes, and likely higher activity in the pathways associated with oxidative phosphorylation and ATP biosynthetic process, was observed in the epilepsy-subtypes, suggesting a high energy expenditure in them. Interestingly, the activity of the above two pathways in most epilepsy-subtypes was lower in the FCD patients, suggesting these subtypes may be more vulnerable to energy deficit in epilepsy. Altogether, transcriptomics is significantly altered in only a few neuronal subtypes in pediatric FCD patient brains. These selective epilepsy-subtypes may play prominent roles in the genesis of pediatric drug-resistant seizure and targeting them may provide new treatment options.

bioinformatics↗

bioRxiv2023

EquiScore: A generic protein-ligand interaction scoring method integrating physical prior knowledge with data augmentation modeling

Developing robust methods for evaluating protein-ligand interactions has been a long-standing problem. Here, we propose a novel approach called EquiScore, which utilizes an equivariant heterogeneous graph neural network to integrate physical prior knowledge and characterize protein-ligand interactions in equivariant geometric space. To improve generalization performance, we constructed a dataset called PDBscreen and designed multiple data augmentation strategies suitable for training scoring methods. We also analyzed potential risks of data leakage in commonly used data-driven modeling processes and proposed a more stringent redundancy removal scheme to alleviate this problem. On two large external test sets, EquiScore outperformed 21 methods across a range of screening performance metrics, and this performance was insensitive to binding pose generation methods. EquiScore also showed good performance on the activity ranking task of a series of structural analogs, indicating its potential to guide lead compound optimization. Finally, we investigated different levels of interpretability of EquiScore, which may provide more insights into structure-based drug design.

bioinformatics↗

bioRxiv2023

A Spatiotemporal Compartmentalization of Glucose Metabolism Guides Mammalian Gastrulation Progression

Gastrulation is considered the sine qua non of embryogenesis, establishing a multidimensional structure and the spatial coordinates upon which all later developmental events transpire. At this time, the embryo adopts a heavy reliance on glucose metabolism to support rapidly accelerating changes in morphology, proliferation, and differentiation. However, it is currently unknown how this conserved metabolic shift maps onto the three-dimensional landscape of the growing embryo and whether it is spatially linked to the orchestrated cellular and molecular processes necessary for gastrulation. Here we identify that glucose is utilised during mouse gastrulation via distinct metabolic pathways to instruct local and global embryonic morphogenesis, in a cell type and stage-specific manner. Through detailed mechanistic studies and quantitative live imaging of mouse embryos, in parallel with tractable in vitro stem cell differentiation models and embryo-derived tissue explants, we discover that cell fate acquisition and the epithelial-to-mesenchymal transition (EMT) relies on the Hexosamine Biosynthetic Pathway (HBP) branch of glucose metabolism, while newly-formed mesoderm requires glycolysis for correct migration and lateral expansion. This regional and tissue-specific difference in glucose metabolism is coordinated with Fibroblast Growth Factor (FGF) activity, demonstrating that reciprocal crosstalk between metabolism and growth factor signalling is a prerequisite for gastrulation progression. We expect these studies to provide important insights into the function of metabolism in other developmental contexts and may help uncover mechanisms that underpin embryonic lethality, cancer, and congenital disease.

developmental biology↗

bioRxiv2022

Generate a new crucian carp (Carassius auratus) strain without intermuscular bones by knocking out bmp6

Elimination of intermuscular bones (IMBs) is vital to the aquaculture industry of cyprinids. In our previous study, we characterized bmp6 as essential in the development of IMBs in zebrafish. Knockout of bmp6 results in the absence of IMBs in zebrafish without affecting growth and reproduction. Therefore, we hypothesized that bmp6 could be used to generate new cyprinid strains without IMBs by gene editing. In this study, we established a gene editing strategy for knocking out the two orthologs of bmp6 in diploid crucian carp (Carassius auratus). We obtained an F3 population with both orthologs knocked out, in which no IMBs were detected by bone staining and X-ray, indicating that the new strain without IMBs (named WUCI strain) was successfully generated. Furthermore, we extensively evaluated the performance of the new strain in growth, reproduction, nutrient components, muscle texture and structure, and metabolites in muscle. The results showed that the WUCI strain grew faster than the wild-type crucian carp at 4-month-age. The reproductive performance and flesh quality did not show significant differences between the WUCI strain and wild-type crucian carp. Moreover, the metabolomics analysis suggested that the muscle tissues of the WUCI strain significantly enriched some metabolites belonging to the Thiamine metabolism, Nicotinate and Nicotinamide Metabolism pathway, which plays beneficial effects in anti-aging, anti-oxidant, and anti-radiation damage. In conclusion, we established a strategy to eliminate IMBs in crucian carp and obtain a WUCI strain whose performance was expected compared to the wild-type crucian carp; meanwhile, the WUCI strain enriched some beneficial metabolites to human health in muscle tissue. This study is the first report that a farmed cyprinid strain without IMBs, which could be stably inherited, was obtained worldwide; it provided excellent germplasm for the cyprinids aquaculture industry and a useful molecular tool for eliminating IMBs in other cyprinids.

genetics↗

bioRxiv2022

Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration

Tools available for reproducible, quantitative assessment of brain correspondence have been limited. We previously validated the anatomical fiducial (AFID) placement protocol for point-based assessment of image registration with millimetric (mm) accuracy. In this data descriptor, we release curated AFID placements for some of the most commonly used structural magnetic resonance imaging templates and datasets. The release of our accurate placements allows for rapid quality control of image registration, teaching neuroanatomy, and clinical applications such as disease diagnosis and surgical targeting. We release placements on individual subjects from four datasets (n = 132 subjects for a total of 15,232 fiducials) and more than 10 brain templates (4,288 fiducials), compiling over 300 human rater hours of annotation. We also validate human rater accuracy of released placements to be within 1-2 mm (using a total of 50,336 Euclidean distances), consistent with prior studies. Our data is compliant with the Brain Imaging Data Structure (BIDS) allowing for facile incorporation into modern neuroimaging analysis pipelines. Data is accessible on GitHub (https://github.com/afids/afids-data).

neuroscience↗

bioRxiv2022

Auxin-independent effects of apical dominance induce temporal changes in phytohormones

The inhibition of shoot branching by the growing shoot tip of plants, termed apical dominance, was originally thought to be mediated by auxin. Recently the importance of the shoot tip sink strength during apical dominance has re-emerged with recent studies highlighting roles for sugars in promoting branching. This raises many unanswered questions on the relative roles of auxin and sugars in apical dominance. Here we show that auxin regulation of cytokinins, which promote branching, is significant only after an initial stage of branching we call bud release. During this early bud release stage, rapid cytokinin increases are associated with enhanced sugars. Auxin may also act through strigolactones which have been shown to suppress branching after decapitation, but here we show that strigolactones do not have a significant effect on initial bud outgrowth after decapitation. We report here that when sucrose or cytokinin is abundant, strigolactones are less inhibitory during the bud release stage compared to later stages and that strigolactone treatment rapidly inhibits cytokinin accumulation in pea axillary buds of intact plants. After initial bud release, we find an important role of gibberellin in promoting sustained bud growth downstream of auxin. We are therefore able to suggest a model of apical dominance that integrates auxin, sucrose, strigolactones, cytokinins and gibberellins and describes differences in signalling across stages of bud release to sustained growth.

plant biology↗

bioRxiv2022

Concurrent measurement of perfusion parameters related to small blood and lymphatic vessels in the human brain using dynamic dual-spin-echo perfusion (DDSEP) MRI

PURPOSEAccumulating evidence from recent studies has indicated the importance of studying the interaction between the microvascular and lymphatic systems in the brain. To date, most imaging methods can only measure blood or lymphatic vessels separately, such as dynamic-susceptibility-contrast (DSC) MRI for blood vessels and DSC MRI in the CSF (cDSC MRI) for lymphatic vessels. An approach that can measure both blood and lymphatic vessels in a single scan will offer the advantages such as halved scan time and contrast dosage. Based on previous works on DSC and cDSC MRI, this study proposes an MRI approach for concurrent measurement of perfusion parameters related to small blood and lymphatic vessels in the brain within one single scan. METHODSBloch simulations were performed to optimize a dual-echo sequence for the measurement of gadolinium(Gd)-induced blood and CSF signal changes using a short and a long echo time, respectively. MRI experiments were performed in healthy subjects to evaluate the dual-echo approach by comparing it with existing separate methods. RESULTSThe proposed method showed consistent results in human brains as previous studies using separate methods. Signal changes from small blood vessels occurred faster than lymphatic vessels after intravenous Gd-injection. CONCLUSIONGd-induced signal changes in blood and CSF can be detected simultaneously in healthy subjects with the proposed sequence. To the best of our knowledge, this may be the first study in which the temporal difference in Gd-induced signal changes from small blood and lymphatic vessels after intravenous Gd-injection was measured in the same human subjects.

neuroscience↗

bioRxiv2022

Successful working memory linked to theta connectivity patterns in the hippocampal-entorhinal circuit

Working memory (WM) is the ability to actively maintain information for a short time and is central to human behavior. Rodent studies have proposed that hippocampal-entorhinal communication supports WM maintenance. However, the exact neural mechanisms of this interaction in WM remains unclear in humans. To address these questions, we combined machine learning analyses with intracranial electroencephalography (iEEG) recordings from the hippocampus and the entorhinal cortex (EC) in human participants, who maintained a set of letters in their WM. We found that WM maintenance was accompanied by elevated bidirectional hippocampal-EC information exchange via the theta band (2-8 Hz) and bidirectional cross-region theta-gamma phase-amplitude coupling (PAC). Further decoding analyses showed that the unidirectional inter-regional communication, with both theta oscillations in the hippocampus modulating EC gamma activity and theta band-coordinated information flow from the hippocampus, could decode correct performance at the level of participants. Taken together, our results demonstrate that theta functional coupling in the hippocampal-EC supports the maintenance of WM information via a specific pattern of frequency and direction. This connectivity-based coding could shed light on the neural mechanisms of WM processing. SignificanceRecent studies suggest a role for the hippocampus in working memory. How does the hippocampus coordinate with other brain regions to retain working memory information? The entorhinal cortex (EC) is the main gateway for information between the hippocampus and neocortex. To delineate whether (and how) the hippocampus and the entorhinal cortex interact during working memory and whether such interaction supports successful working memory, we used machine learning analyses of human intracranial EEG recordings while patients performed working memory tasks. Our results suggest that the human hippocampal-EC circuit supports working memory and is maintained in specific connectivity patterns, with a theta band (2-8 Hz)-coordinated unidirectional influence from the hippocampus to the EC. Our findings reveal that dynamic unidirectional interactions within the hippocampal-EC circuit underlie working memory and can contribute to a mechanistic circuit understanding of working memory.

neuroscience↗

bioRxiv2022

Temporal integration of rod signals in luminance and chromatic pathways

We assessed how rod excitation (R) affects luminance (L+M+S) and chromatic [L/(L+M)] reaction times (RTs). A four-primary display based on the overlapped images of two spectrally-modified monitors, which allowed specific or combined [L+M+S+R, L/(L+M) + R] photoreceptor stimulation, was used to present a C-target stimulus differing from the background only by the selected stimulation. For the luminance pathway, rod input increased RTs, suggesting a suppressive rod-cone interaction. The responses of the chromatic pathway were faster when rods were involved, suggesting a major role of rods in mesopic color perception.

physiology↗

bioRxiv2022

Comparing flickering and pulsed chromatic pupil light responses

Protocols for chromatic pupil light reflex (PLR) testing considered mostly pulsed stimulation (pPLR). A more sophisticated and promising technique is based on the PLR to flickering stimulation (fPLR). Our aim was to compare fPLR and pPLR parameters in order to validate fPLR paradigm. Two different experiments were carried out in young participants to compare parameters of chromatic pupillary measurements under flickering and pulsed conditions. We found that the fPLR amplitude parameter was significantly associated with pPLR transient constriction parameter. Also, for some conditions, typical pulse parameters can be identified directly in the fPLR recordings.

physiology↗